distilbert-base-uncased-distilled-dtkd-clinc
This model is a fine-tuned version of distilbert-base-uncased on the clinc_oos dataset. It achieves the following results on the evaluation set:
- Loss: 0.0655
- Accuracy: 0.9319
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6996 | 1.0 | 318 | 0.4150 | 0.5790 |
0.3134 | 2.0 | 636 | 0.2040 | 0.8381 |
0.1843 | 3.0 | 954 | 0.1330 | 0.8952 |
0.1322 | 4.0 | 1272 | 0.1032 | 0.9119 |
0.1053 | 5.0 | 1590 | 0.0858 | 0.9213 |
0.0908 | 6.0 | 1908 | 0.0771 | 0.9258 |
0.0813 | 7.0 | 2226 | 0.0710 | 0.9287 |
0.0754 | 8.0 | 2544 | 0.0681 | 0.9310 |
0.0717 | 9.0 | 2862 | 0.0660 | 0.9310 |
0.0701 | 10.0 | 3180 | 0.0655 | 0.9319 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.13.1+cu116
- Datasets 1.16.1
- Tokenizers 0.10.3
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